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1.6 Metric Baseline

Describe setting a metric baseline

A metric baseline is a reference point that represents the normal or expected performance of a network or system. It is established by collecting and analyzing performance data over a specific period. Baselines are essential for network monitoring and troubleshooting as they allow you to:

  • Assess performance: Compare current measurements against the baseline to determine if the network is performing as expected.
  • Detect anomalies: Quickly identify deviations from the baseline that may indicate a performance issue or security threat.
  • Troubleshoot problems: Use the baseline to understand the magnitude of a problem and how it differs from normal behavior.

Key Concepts

Establishing a metric baseline involves several key steps:

  1. Define metrics and objectives: Determine which metrics are crucial for monitoring network health, such as bandwidth utilization, CPU usage, or application response time. Clearly define what you aim to achieve by establishing a baseline for these metrics.

  2. Choose a time period: Select a timeframe for data collection that captures representative network behavior, including both peak and off-peak traffic patterns. The length of this period depends on the stability and variability of the network environment.

  3. Collect data: Gather relevant data points from appropriate sources, such as ThousandEyes tests, SNMP monitoring, or network device logs.

  4. Analyze data: Examine the collected data to identify patterns, trends, and typical performance levels. Use statistical methods to determine average values, percentiles, or standard deviations for each metric.

  5. Establish baseline: Based on the data analysis, set a reference point that represents the normal or expected performance for each metric.

  6. Monitor and update: Continuously monitor network metrics over time and update the baseline as network conditions or requirements evolve.

  7. Define alert thresholds: Set thresholds based on the baseline values to trigger alerts when metrics deviate significantly from the expected range. This allows you to proactively detect and address potential performance issues.

Resources

Sample Questions

1.6 Question 1

A network administrator wants to establish a baseline for CPU utilization on their core routers. Which data source would be MOST appropriate for this purpose?

  • A) DNS resolution time from ThousandEyes tests
  • B) HTTP Server response times from ThousandEyes tests
  • C) SNMP data collected from the routers
  • D) Network path visualization from ThousandEyes tests

1.6 Question 2

What is an important consideration when choosing a time period for collecting data to establish a baseline for interface utilization on a critical network link?

  • A) Selecting the time period with the lowest network traffic volume.
  • B) Ensuring the time period aligns with the organization's financial year.
  • C) Capturing both peak and off-peak traffic patterns for a representative view.
  • D) Limiting the time period to minimize the amount of data that needs to be analyzed.